guess (version 0.7.0)

transmat: transmat: Cross-wave transition matrix

Description

Prints Cross-wave transition matrix and returns the vector behind the matrix. Missing values are treated as don't know responses by default. Set `na_as = "missing"` when they instead represent structural missingness.

Usage

transmat(
  pre_test_var,
  pst_test_var,
  subgroup = NULL,
  force9 = FALSE,
  na_as = c("dk", "missing"),
  missing_action = c("omit", "error")
)

Value

a numeric vector. Assume 1 denotes correct, 0 incorrect, and d/DK an observed don't know. When there is no don't know option and no missing, the entries are: x00, x10, x01, x11 When there is a don't know option, the entries of the vector are: x00, x10, xd0, x01, x11, xd1, xd0, x1d, xdd

Arguments

pre_test_var

Required. A vector carrying pre-test scores of a particular item. Only

pst_test_var

Required. A vector carrying post-test scores of a particular item

subgroup

Optional. A Boolean vector indicating rows of the relevant subset.

force9

Optional. There are cases where DK data doesn't have DK. But we need the entire matrix. By default it is FALSE.

na_as

Classification of NA responses: `"dk"` (the default) treats them as observed don't know responses; `"missing"` treats them as structural missingness.

missing_action

How to handle structural missingness: `"omit"` excludes incomplete pairs and `"error"` rejects them.

Examples

pre_test_var <- c(1, 0, 0, 1, 0, 1, 0)
pst_test_var <- c(1, 0, 1, 1, 0, 1, 1)
transmat(pre_test_var, pst_test_var)

# With NAs
pre_test_var <- c(1, 0, 0, 1, "d", "d", 0, 1, NA)
pst_test_var <- c(1, NA, 1, "d", 1, 0, 1, 1, "d")
transmat(pre_test_var, pst_test_var)